What You Need to Know Before
You Start

Starts 4 June 2026 19:12

Ends 4 June 2026

00 Days
00 Hours
00 Minutes
00 Seconds
course image

Secure AI Interpret and Protect Models

Unlock proactive AI security by mastering adversarial training, input sanitization, and differential privacy to build resilient models from the ground up.
Coursera via Coursera

Coursera

2868 Courses


3 hours 25 minutes

Optional upgrade avallable

Not Specified

Progress at your own speed

Paid Course

Optional upgrade avallable

Overview

Ever wonder if your smart AI is actually secure? In this course, we'll ditch the dry theory to show you how to build genuinely resilient AI systems from the ground up, making security a core part of your design, not just an afterthought.

You'll begin by stepping into the role of an AI Security Architect, running a “pre-mortem” to think like an attacker and neutralize threats before they even happen. Through focused videos and exercises, you’ll master essential defenses like blocking bad data with input sanitization, ‘vaccinating’ your model against attacks with adversarial training, and protecting user data with differential privacy.

This all culminates in a hands-on lab where you'll personally fix a vulnerable model and prove its new resilience. The main goal is to shift your mindset from reactive patching to proactive design, so you’ll walk away with the real-world skills to analyze defense strategies, successfully harden a model in a lab, and design a comprehensive security plan for any new AI project.

Syllabus

  • The Attacker's Playbook: Understanding AI Vulnerabilities
  • This module introduces the fundamental concept that AI models are attack surfaces. You will learn to think like an adversary, exploring the primary categories of attacks—evasion, data poisoning, and model extraction—and see how they exploit model weaknesses with real-world examples.
  • Building the Shield: Proactive Defense Strategies
  • Moving from offense to defense, this module focuses on building security directly into your AI systems. You will learn to implement and configure robust, proactive defense mechanisms like adversarial training, input sanitization, and differential privacy to create models that are resilient by design.
  • Adversarial Testing and the Continuous Cycle
  • A defense is only effective if it's tested. In this final module, you will master the art of AI "Red Teaming" by designing and executing simulated attacks to validate your security measures. You will learn to evaluate model resilience and embrace the continuous security lifecycle required to stay ahead of emerging threats.

Taught by

Starweaver and Rifat Erdem Sahin


Subjects

Computer Science